Image reconstruction in Compressed Sensing based on single-level DWT

Author

Jin Zhang ; Ling Xia ; Mei Huang ; Guangrui Li

Author_Institution

Sch. of Electr. & Inf. Eng., XiHua Univ., Chengdu, China

fYear

2014

fDate

8-9 May 2014

Firstpage

941

Lastpage

944

Abstract

Wavelet transform is commonly used in Compressed Sensing. To improve the image reconstruction quality in CS based on single-level DWT, two improved methods are proposed. Row-column average method processes the row vectors and column vectors of the coefficient matrices separately to get two reconstructed images, and then takes the average of them as the final result. Threshold method sets a threshold to improve the sparsity of row vectors or column vectors of the coefficient matrices. Experimental results show that the two methods can significantly improve the quality of reconstructed images.

Keywords

compressed sensing; discrete wavelet transforms; image reconstruction; matrix algebra; vectors; CS; coefficient matrices; column vectors; compressed sensing; image reconstruction quality; row vectors; row-column average method; single-level DWT; threshold method; wavelet transform; Compressed sensing; Educational institutions; Image coding; Image reconstruction; PSNR; Sensors; Compressed Sensing; image reconstruction; single-level DWT;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Computer and Applications, 2014 IEEE Workshop on

Conference_Location

Ottawa, ON

Type

conf

DOI

10.1109/IWECA.2014.6845776

Filename

6845776